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Record W4361026261 · doi:10.1016/s1470-2045(23)00067-0

Multinational Association of Supportive Care in Cancer (MASCC) clinical practice guidelines for the prevention and management of acute radiation dermatitis: international Delphi consensus-based recommendations

2023· review· en· W4361026261 on OpenAlexaff
Tara Behroozian, Pierluigi Bonomo, Partha Patel, Lauren Kanee, Samuel Finkelstein, Corina van den Hurk, Edward Chow, Julie Ryan Wolf, Suvam Banerjee, Carlotta Becherini, Christine B. Boers‐Doets, Marta Carlesimo, Gemma Caro, Maria Caterina Fortuna, Adrian Wai Chan, Lorraine C. Drapek, Azael Freites‐Martínez, Satoshi Hirakawa, Emily H. Smith, Nicola Alessandro Iacovelli, Bernice Y. Kwong, Shing Fung Lee, Alina Markova, Robert F. Miller, Gustavo Nader Marta, Silvina Pugliese, Claire Marie Reyes Habito, Jolien Robijns, Viola Salvestrini, Leonard Christopher Schmeel, Mateusz Spałek, Mark Trombetta, Henry C. Y. Wong

Bibliographic record

VenueThe Lancet Oncology · 2023
Typereview
Languageen
FieldMedicine
TopicEffects of Radiation Exposure
Canadian institutionsUniversity of OttawaUniversity of TorontoMcMaster University
FundersNational Cancer InstituteUniversity of Rochester
KeywordsMultinational corporationMedicineDelphi methodDelphiClinical PracticeFamily medicineIntensive care medicineMedical physicsPolitical science

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.060
metaresearch head score (Gemma)0.079
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.060
Threshold uncertainty score0.319

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0600.079
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.008
Bibliometrics0.0100.008
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0050.004
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0050.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.216
GPT teacher head0.578
Teacher spread0.361 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations117
Published2023
Admission routes1
Has abstractno

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Same venueThe Lancet OncologySame topicEffects of Radiation ExposureFrench-language works237,207